Adaptive Multiple Input Multiple Output PID Control System for Industrial Turbines

ABSTRACT

The subject matter of this specification can be embodied in, among other things, a method that includes receiving, at a ratio controller, turbine response values based on first process output value based on a first control parameter and a first process input value, and a second process output value based on a second control parameter and a second process input value, providing the first process input value as a predetermined first constant set point value while varying the second process input value, receiving updated turbine response values, determining at least one third control parameter, providing the third control parameter as the second control parameter, providing the second process input value as a predetermined second constant set point value while varying the first process input value, receiving updated turbine response values, determining at least one fourth control parameter, and providing the fourth control parameter as the first control parameter.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of priority to U.S. ProvisionalApplication Ser. No. 62/217,566, filed on Sep. 11, 2015, the contents ofwhich are hereby incorporated by reference.

TECHNICAL FIELD

This specification relates to controlling industrial turbines.

BACKGROUND

A turbine is a rotary mechanical device that converts energy from afluid flow to work, such as by providing thrust or rotary mechanicalpower. A turbine is a turbomachine with at least one moving part calleda rotor assembly, which is a shaft or drum onto which blades areattached. Moving fluid acts on the blades so that they move and impartrotational energy to the rotor.

A proportional-integral-derivative (PID) controller is a control loopfeedback system that is widely used in industrial control systems. A PIDcontroller determines the difference between a measured process variableand a desired set point and calculates an error value. The PIDcontroller adjusts process control outputs to reduce the error value.

Tuning of PID controllers can be a difficult task, especially inapplications such as turbine control where multiple, possiblyconflicting, performance objectives such as fast transient response andhigh stability of the turbine output are desired. Tuning of PIDcontrollers can also be difficult when the turbine is unloaded, sinceunloaded turbines are systems with little damping and high acceleration,which are unusual conditions within the process control industry. Inpractice, such applications can exceed the skills or training of turbineoperations personnel, and PID tuning configurations are thus oftenadjusted repeatedly through trial-and-error until the system provides anacceptable, but not always optimal, level of performance.

SUMMARY

In general, this document describes controlling industrial turbines.

In a first aspect, a method for operating a turbine includes receiving,at a ratio controller, one or more turbine response values based on afirst process output value (S_(out)) of a first actuator controller, thefirst process output value based on a first process input value (S_(in))and at least one first control parameter selected from a group includinga proportional gain value, an integral gain value, and a derivative gainvalue, wherein the first actuator controller includes a first parametercontroller, and a second process output value (P_(out)) of a secondactuator controller, the second process output value based on a secondprocess input value (P_(in)) and at least one second control parameterselected from the group, wherein the second actuator controller includesa second parameter controller. The method also includes providing, bythe ratio controller and to the first actuator controller, the firstprocess input value as a predetermined first constant set point value,varying, by the ratio controller and to the second actuator controller,the second process input value to a plurality of predetermined first setpoint values, receiving, by the second parameter controller and for oneor more of the first set point values, one or more first updated turbineresponse values as the turbine response values, determining, by thesecond parameter controller, at least one third control parameterselected from the group based on the turbine response values, providing,by the second parameter controller and to the second actuatorcontroller, the third control parameter as the second control parameter,providing, by the ratio controller and to the second actuatorcontroller, the second process input value as a predetermined secondconstant set point value, varying, by the ratio controller and to thefirst actuator controller, the first process input value to a pluralityof predetermined second set point values, receiving, by the firstparameter controller and for one or more of the second set point values,one or more second updated turbine response values as the turbineresponse values, determining, by the first parameter controller, atleast one fourth control parameter selected from the group based on theturbine response values, and providing, by the first parametercontroller and to the first actuator controller, the fourth controlparameter as the first control parameter.

Various implementations can include some, all, or none of the followingfeatures. The method can include controlling, by the first parametercontroller and the second parameter controller, the turbine based on thefirst process output value and the second process output value. Themethod can include determining a first control output value (HP) basedon the first process output value (S_(out)), the second process outputvalue (P_(out)), and one or more ratio parameters (K_(x)), determining asecond control output value (LP) based on the first process output value(S_(out)), the second process output value (P_(out)), and the ratioparameters, and controlling, by the ratio controller, the turbine basedon the first control output value and the second control output value.The one or more ratio parameters (K_(x)) can include a collection ofratio parameters K₁, K₂, K₃, K₄, K₅, and K₆, the first control output(HP) can be given by the equation HP=K₁S_(out)+K₂P_(out)+K₃, and thesecond control output (LP) can be given by the equationLP=K₄S_(out)+K₅P_(out)+K₆. The first parameter controller can control afirst component of the turbine effecting the turbine response values,and the second parameter controller controls a second component of theturbine effecting the turbine response values.

In a second aspect, a turbine controller includes an input port, anoutput port, a ratio controller, memory storing instructions that areexecutable, and one or more processing devices to execute theinstructions to perform operations that include receiving, at the ratiocontroller, one or more turbine response values based on a first processoutput value (S_(out)) of a first actuator controller, the first processoutput value based on a first process input value (S_(in)) and at leastone first control parameter selected from a group including aproportional gain value, an integral gain value, and a derivative gainvalue, wherein the first actuator controller includes a first parametercontroller, and a second process output value (P_(out)) of a secondactuator controller, the second process output value based on a secondprocess input value (P_(in)) and at least one second control parameterselected from the group, wherein the second actuator controller includesa second parameter controller. The operations also include providing, bythe ratio controller and to the first actuator controller, the firstprocess input value as a predetermined first constant set point value,varying, by the ratio controller and to the second actuator controller,the second process input value to a plurality of predetermined first setpoint values, receiving, by the second parameter controller and for oneor more of the first set point values, one or more first updated turbineresponse values as the turbine response values, determining, by thesecond parameter controller, at least one third control parameterselected from the group based on the turbine response values, providing,by the second parameter controller and to the second actuatorcontroller, the third control parameter as the second control parameter,providing, by the ratio controller and to the second actuatorcontroller, the second process input value as a predetermined secondconstant set point value, varying, by the ratio controller and to thefirst actuator controller, the first process input value to a pluralityof predetermined second set point values, receiving, by the firstparameter controller and for one or more of the second set point values,one or more second updated turbine response values as the turbineresponse values, determining, by the first parameter controller, atleast one fourth control parameter selected from the group based on theturbine response values, and providing, by the first parametercontroller and to the first actuator controller, the fourth controlparameter as the first control parameter.

Various embodiments can include some, all, or none of the followingfeatures. The operations can include controlling, by the first parametercontroller and the second parameter controller, the turbine based on thefirst process output value and the second process output value. Theoperations can include determining a first control output value (HP)based on the first process output value (S_(out)), the second processoutput value (P_(out)), and one or more ratio parameters (K_(x)),determining a second control output value (LP) based on the firstprocess output value (S_(out)), the second process output value(P_(out)), and the ratio parameters, and controlling, by the ratiocontroller, the turbine based on the first control output value and thesecond control output value. The one or more ratio parameters (K_(x))can include a collection of ratio parameters K₁, K₂, K₃, K₄, K₅, and K₆,the first control output (HP) can be given by the equationHP=K₁S_(out)+K₂P_(out)+K₃, and the second control output (LP) can begiven by the equation LP=K₄S_(out)+K₅P_(out)+K₆. The first parametercontroller can control a first component of the turbine effecting theturbine response values, and the second parameter controller can controla second component of the turbine effecting the turbine response values.

In a third aspect, a turbine system includes a first process controllerconfigured to perform a control algorithm based on at least one firstcontrol parameter selected from a group including a proportional gainvalue, an integral gain value, and a derivative value, a second processcontroller configured to perform a control algorithm based on at leastone second control parameter selected from a group including aproportional gain value, an integral gain value, and a derivative value,a ratio controller configured to perform a parameter adjustmentalgorithm, a turbine having assembled thereto a turbine output sensor incommunication with the first process controller, the second processcontroller, and the ratio controller, wherein the parameter adjustmentalgorithm is configured to perform operations that include receiving, atthe ratio controller, one or more turbine response values based on afirst process output value (S_(out)) of a first actuator controller, thefirst process output value based on a first process input value (S_(in))and at least one first control parameter selected from a group includinga proportional gain value, an integral gain value, and a derivative gainvalue, wherein the first actuator controller includes a first parametercontroller and a second process output value (P_(out)) of a secondactuator controller, the second process output value based on a secondprocess input value (P_(in)) and at least one second control parameterselected from the group, wherein the second actuator controller includesa second parameter controller. The operations also include providing, bythe ratio controller and to the first actuator controller, the firstprocess input value as a predetermined first constant set point value,varying, by the ratio controller and to the second actuator controller,the second process input value to a plurality of predetermined first setpoint values, receiving, by the second parameter controller and for oneor more of the first set point values, one or more first updated turbineresponse values as the turbine response values, determining, by thesecond parameter controller, at least one third control parameterselected from the group based on the turbine response values, providing,by the second parameter controller and to the second actuatorcontroller, the third control parameter as the second control parameter,providing, by the ratio controller and to the second actuatorcontroller, the second process input value as a predetermined secondconstant set point value, varying, by the ratio controller and to thefirst actuator controller, the first process input value to a pluralityof predetermined second set point values, receiving, by the firstparameter controller and for one or more of the second set point values,one or more second updated turbine response values as the turbineresponse values, determining, by the first parameter controller, atleast one fourth control parameter selected from the group based on theturbine response values, and providing, by the first parametercontroller and to the first actuator controller, the fourth controlparameter as the first control parameter.

Various embodiments can include some, all, or none of the followingfeatures. The operations can also include controlling, by the firstparameter controller and the second parameter controller, the turbinebased on the first process output value and the second process outputvalue. The operations can include determining, by a ratio controller, atone or more ratio parameters (K_(x)), determining a first control outputvalue (HP) based on the first process output value (S_(out)), the secondprocess output value (P_(out)), and the ratio parameters, determining asecond control output value (LP) based on the first process output value(S_(out)), the second process output value (P_(out)), and the ratioparameters, and controlling, by the ratio controller, the turbine basedon the first control output value and the second control output value.The one or more ratio parameters (K_(x)) can include a collection ofratio parameters K₁, K₂, K₃, K₄, K₅, and K₆, the first control output(HP) can be given by the equation HP=K₁S_(out)+K₂P_(out)+K₃, and thesecond control output (LP) can be given by the equationLP=K₄S_(out)+K₅P_(out)+K₆. The first parameter controller can control afirst component of the turbine effecting the turbine response values,and the second parameter controller can control a second component ofthe turbine effecting the turbine response values.

In a fourth aspect, a computer readable medium stores instructions that,when executed by one or more processors, cause the one or moreprocessors to perform operations including receiving, at a ratiocontroller, one or more turbine response values based on a first processoutput value (S_(out)) of a first actuator controller, the first processoutput value based on a first process input value (S_(in)) and at leastone first control parameter selected from a group including aproportional gain value, an integral gain value, and a derivative gainvalue, wherein the first actuator controller includes a first parametercontroller and a second process output value (P_(out)) of a secondactuator controller, the second process output value based on a secondprocess input value (P_(in)) and at least one second control parameterselected from the group, wherein the second actuator controller includesa second parameter controller. The operations also include providing, bythe ratio controller and to the first actuator controller, the firstprocess input value as a predetermined first constant set point value,varying, by the ratio controller and to the second actuator controller,the second process input value to a plurality of predetermined first setpoint values, receiving, by the second parameter controller and for oneor more of the first set point values, one or more first updated turbineresponse values as the turbine response values, determining, by thesecond parameter controller, at least one third control parameterselected from the group based on the turbine response values, providing,by the second parameter controller and to the second actuatorcontroller, the third control parameter as the second control parameter,providing, by the ratio controller and to the second actuatorcontroller, the second process input value as a predetermined secondconstant set point value, varying, by the ratio controller and to thefirst actuator controller, the first process input value to a pluralityof predetermined second set point values, receiving, by the firstparameter controller and for one or more of the second set point values,one or more second updated turbine response values as the turbineresponse values, determining, by the first parameter controller, atleast one fourth control parameter selected from the group based on theturbine response values, and providing, by the first parametercontroller and to the first actuator controller, the fourth controlparameter as the first control parameter.

Various embodiments can include some, all, or none of the followingfeatures. The operations can also include controlling, by the firstparameter controller and the second parameter controller, the turbinebased on the first process output value and the second process outputvalue. The operations can include determining, by a ratio controller, atone or more ratio parameters (K_(x)), determining a first control outputvalue (HP) based on the first process output value (S_(out)), the secondprocess output value (P_(out)), and the ratio parameters, determining asecond control output value (LP) based on the first process output value(S_(out)), the second process output value (P_(out)), and the ratioparameters, and controlling, by the ratio controller, the turbine basedon the first control output value and the second control output value.The one or more ratio parameters (K_(x)) can include a collection ofratio parameters K₁, K₂, K₃, K₄, K₅, and K₆, the first control output(HP) can be given by the equation HP=K₁S_(out)+K₂P_(out)+K₃, and thesecond control output (LP) can be given by the equationLP=K₄S_(out)+K₅P_(out)+K₆. The first parameter controller can control afirst component of the turbine effecting the turbine response values,and the second parameter controller can control a second component ofthe turbine effecting the turbine response values.

The systems and techniques described herein may provide one or more ofthe following advantages. First, a system can provide for automatedadjustment of proportional, integral, and derivative gain parameters ofmultiple input, multiple output (MIMO) process controllers to achieve apredetermined operation of a turbine. Second, the system can provideMIMO speed and pressure control of a turbine. Third, the system canprovide MIMO load and pressure control of a gas or steam turbine,utilizing speed droop. Fourth, the system can provide MIMO load controlof a gas or steam turbine, utilizing load droop. Fifth, the system canprovide MIMO inlet/exhaust and pressure control of a steam turbinepulling a vacuum. Sixth, the system can provide MIMO extraction controlof a steam turbine.

The details of one or more implementations are set forth in theaccompanying drawings and the description below. Other features andadvantages will be apparent from the description and drawings, and fromthe claims.

DESCRIPTION OF DRAWINGS

FIG. 1 is a schematic diagram that shows an example of an industrialturbine control system.

FIG. 2 is a block diagram that shows an example of a parametercontroller.

FIG. 3 is flow chart that shows an example of a process for determiningPID control parameters.

FIG. 4 is flow chart that shows an example of a process for controllingindustrial turbines.

FIG. 5 is flow chart that shows another example of a process fordetermining PID control parameters.

FIG. 6 is flow chart that shows another example of a process fordetermining PID control parameters.

FIG. 7 is a chart showing an example result of tuning an industrialturbine controller having an initially underdamped response.

FIG. 8 is a chart showing an example result of tuning an industrialturbine controller having an initially overdamped response.

FIG. 9 is a schematic diagram that shows an example of anotherindustrial turbine control system.

FIG. 10 is a block diagram of an example turbine controller.

FIG. 11 is a flow diagram of an example process for selecting a turbinecontroller operational mode.

FIG. 12 is a block diagram of an example turbine controller in a normaloperational mode.

FIG. 13 is a flow diagram of an example process for tuning multipleactuator controllers.

FIG. 14 is a block diagram of an example turbine controller in a tuningmode.

FIG. 15 is a flow diagram of an example process stage for tuningmultiple actuator controllers.

FIG. 16 is a block diagram of an example turbine controller in anothertuning mode.

FIG. 17 is a flow diagram of another example process stage for tuningmultiple actuator controllers.

FIG. 18 is a flow diagram of another example process stage for tuningmultiple actuator controllers.

FIG. 19 is a flow diagram of another example process stage for tuningmultiple actuator controllers.

FIG. 20 is a flow diagram of another example process stage for tuningmultiple actuator controllers.

FIGS. 21A and 21B are flow diagrams of another example process fortuning multiple actuator controllers.

FIG. 22 is a schematic diagram of an example of a generic computersystem.

FIG. 23 is a diagram of an example steam map.

DETAILED DESCRIPTION

This document describes systems and techniques for multiple input,multiple output (MIMO) control of industrial turbines. Industrialturbines can be controlled using proportional (P), proportional-integral(PI), and proportional-integral-derivative (PID) controllers. Tuning P,PI, and PID controllers, however, can be a challenge. For example,because industrial turbines can present demanding control challenges,and/or because the dynamic behavior of industrial turbines may not be anobvious or intuitive subject for some turbine operators.

FIG. 1 is a schematic diagram that shows an example of an industrialturbine control system 100. A turbine assembly 110 includes a turbine112, and a collection of one or more controllable inputs 114 forcontrolling the flow of a collection of one or more fluid or steamsupplies 116 to the turbine 112. By controllably adjusting thecontrollable inputs 114 to control the flows of the steam/fluid supplies116 to the turbine 112, the rotational speed, load, acceleration,deceleration, and other performance parameters of the turbine 112 can becontrollably adjusted.

In some embodiments, the turbine 112 can be a gas turbine or other formof combustion-driven turbine. In such embodiments, the controllableinputs 114 can include pumps, valves, injectors, and combinations ofthese and other devices for controlling the flows of the fluid supplies116 such as gasses (e.g., natural gas, hydrogen, oxygen, propane,methane, air) and/or liquids (e.g., fuel, water) to the turbine 112. Insome embodiments, the turbine 112 can be a steam turbine. In suchembodiments, the controllable inputs 114 can include pumps, valves,injectors, and combinations of these and other devices for controllingthe flow of the fluid supply 116, in the form of steam, to the turbine112.

In the example system shown in FIG. 1, the controllable inputs 114 areadjusted by a proportional-integral-derivative (PID) controller 120. ThePID controller 120 adjusts the controllable inputs 114 based on an inputparameter 122 (e.g., desired turbine speed), a feedback signal 132provided by a sensor 130 configured to sense an output 118 of theturbine 112, and a collection of control parameters 124 in a closed-loopfeedback control system. In some embodiments, the sensor 130 can be aspeed sensor configured to sense the rotational speed of the turbine112, and provide a speed signal as the feedback signal 132 to the PIDcontroller 120. In some embodiments, the sensor 130 can be atemperature, pressure, vibration, or any other appropriate sensor thatcan be used to sense a parameter of the turbine assembly 110 and providethe feedback signal 132 in response to the sensed parameter. In someembodiments, the PID controller 120 can be a P controller or a PIcontroller instead, or the PID controller 120 can be configured as a PIor P controller (e.g., by setting D and/or I gains to zero).

The performance of the turbine assembly 110 is evaluated as a comparisonbetween how rapidly and/or accurately the feedback signal 132 tracks theinput parameter 122. For example, the input parameter 122 can be adesired speed setting, and the control parameters 124 can affect howclosely the speed of the turbine 112 matches a desired steady-statespeed, and/or the control parameters 124 can affect how closely thespeed of the turbine 112 is able to change to meet a newly establisheddesired speed within a predetermined amount of time (e.g., an overdampedresponse) and within a predetermined amount of speed overshoot (e.g., anunderdamped response). Examples of overdamped and underdamped responsesare discussed further in connection with the descriptions of FIGS. 7 and8.

In the example system shown in FIG. 1, the input parameter 122 and thefeedback signal 132 are also provided to a parameter controller 140. Theparameter controller 140 compares the input parameter 122 to thefeedback signal 132 to determine a set of control parameters 142. Theparameter controller 140 can also generate a disturbance parameter andprovide it as the input parameter 122 to the PID controller 120, orcontrol the output of the PID directly, and analyze the response of theturbine 112 through the feedback signal 132. For example, the parametercontroller 140 can change a desired speed from a first desired speed toa second desired speed as a step function, and can monitor the output ofa speed sensor to analyze how accurately and quickly the turbineassembly 110 responds. The parameter controller 140 can also adjust theactuator directly, and analyze the system.

By comparing the input parameter 122 to the feedback signal 132, theparameter controller 140 can execute a parameter adjustment algorithm144 to determine a set of control parameters 142. The parametercontroller 140 provides the control parameters 142 to the PID controller120 for use as the control parameters 124, for controlling the turbineassembly 110.

In some embodiments, the system 100 can provide load control of a gas orsteam turbine utilizing speed droop. In some embodiments, the system 100can provide load control of a gas or steam turbine utilizing load droop.For example, droop control can allow individual generators to sharesystem load changes in proportion to their maximum output rating. Forexample, in electricity generation, droop speed control can be a primaryinstantaneous system using net frequency deviations to stably distributeload changes over multiple turbine-driven generators. In someembodiments, pressure control, temperature control, flow control,voltage control, current control, kw control, or combinations of theseand/or other appropriate control types can be utilized to control aturbine.

FIG. 2 is a block diagram that shows an example of the parametercontroller 140 of FIG. 1. The parameter controller 140 includes thecontrol parameters 142 and the parameter adjustment algorithm 144.Included among the control parameters 142 are a proportional (P) gainparameter 210, an integral (I) gain parameter 220, and a derivative gainparameter (D). For user input purposes, rather than derivative, an inputfor a speed derivative ratio (SDR) gain parameter 230, may be provided.The SDR parameter is converted to the derivative parameter by theparameter controller 140 and/or the PID controller 120. A generic formof the parallel PID controller transfer function used by the PIDcontroller 120 is given by the equation:

${H(s)} = {{P\left( {1 + \frac{I}{s}} \right)}\left( {{Ds} + 1} \right)}$

Rather than exposing the derivative term (D) to the user, the PIDcontroller 120 uses the form shown above to allow the user to adjust theSpeed Derivative Ratio, or SDR. In some implementations, the SDRparameter can simplify the task of turbine configuration, while leavingthe fundamental PID structure substantially unchanged, and allows thePID algorithm to use values for the P, I, and D gain parameters.

The SDR parameter 230 is a combination of I and D. In someimplementations, use of the SDR parameter 230 can make tuning of the PIDcontroller 120 easier for turbine operators or other users. The userselects the SDR value to indicate whether input or feedback dominantbehavior is desired. For examples in which the value of the SDRparameter 230 is greater than 1, but less than 100, the system isconsidered as being “feedback dominant”, and the equation representingthe output of the PID controller 120 is:

${{Out} = {{\frac{1}{{\left( \frac{1}{I} \right)s} + 1}{Feedback}} + {\frac{{\left( \frac{1}{{SDR} \cdot I} \right)s} + 1}{{\left( \frac{0.2}{{SDR} \cdot I} \right)s} + 1}{P \cdot {error}}}}},{and}$D = 1/(SDR * I)

In the foregoing equation, “error” represents the error between the setpoint and the process inputs, and “Out” represents the output of the PIDfunction, which is typically the demand to the actuator.

In feedback dominant mode, the I term is implemented in the integratorfeedback, and the control will be less sensitive to input noise. In someimplementations, this mode can be useful for parameters which are mostlyinfluenced by fuel demand, because the PID controller 120 can limit thefuel demand of other modes of control even if the set point of the PIDcontroller 120 has not been exceeded. In some implementations,temperature controls can use this mode because temperature feedback isgenerally not fast enough to prevent an over-temperature condition evenwhen extra derivative gain is provided in the input.

For examples in which the value of the SDR parameter 230 is equal orless than 1, but greater than 0.01, the system is considered as being“input dominant”, and the equation representing the output of the PIDcontroller 120 is:

${{Out} = {{\frac{1}{{\left( \frac{SDR}{I} \right)s} + 1}{Feedback}} + {\frac{{\left( \frac{1}{I} \right)s} + 1}{{\left( \frac{0.2 \cdot {SDR}}{I} \right)s} + 1}{{SDP} \cdot P \cdot {error}}}}},{and}$D = SDR/I

In input dominant mode, the D term is implemented in the integratorfeedback, and the control will be more sensitive to its input and lesssensitive to its feedback. This configuration causes the PID controller120 to take corrective action before reaching the set point. In someimplementations, this mode can be used when the parameter beingcontrolled is influenced by an external disturbance. The “inputdominant” mode responds well to external disturbances, but has anincreased sensitivity to noise coming in with the controlled parameter.Again, in the present example, “error” represents set point feedbackerror, and “Out” represents the output of the PID function.

For examples in which the value of the SDR parameter 230 is less than orequal to 0.01 or greater than or equal to 100, the equation in paragraph59 is used, with D set to 0. In both of these cases, the PID controller120 operates as a PI controller, rather than a PID controller. Theparameter controller 140 uses the parameter adjustment algorithm 144 todetermine the P and I, or P, I, and SDR values, and provides them to thePID controller 120 for use as the control parameters 124.

While the transfer function for the input dominant mode and the feedbackdominant mode is substantially the same, the difference between the twomodes will be exhibited when the controlled system comes into controlfrom an out of control situation. The selection of the “input dominant”or “feedback dominant” mode is selected by the user, and hassubstantially no effect on a single PID control, has substantially noeffect on a multiple PID control in which one PID is in control, and hassubstantially no effect on the parameter controller functionality. Forthe purposes of the examples discussed here, it does not matter whetherthe system is input or feedback dominant. The two equations inparagraphs [0051] and [0055] above are the same, except when the PIDcontroller 120 is coming into or out of control. As a result, theequation below can be used for further discussions, without loss ofaccuracy.

${H(s)} = {{P\left( {1 + \frac{I}{s}} \right)}\left( {{Ds} + 1} \right)}$

For the purpose of the following discussion, it does matter if thecontrol is a PI or PID controller, as the gains are calculateddifferently. For a PID control, P, I, and D are calculated. For a PIcontrol, D is set to 0, and P is lowered accordingly. For a P control, Iand D are set to 0 and P is lowered further. In some implementations,nominal values for P, I, and D may vary from system to system. Forexample, P may vary inversely with the input variable scaling and range,and I and D may vary with the response of the system being controlled.As discussed previously, D is a function of SDR. P, I, and SDR vary withthe desired response by the user. For example, some control loops mayrequire very fast response, while other control loops may not tolerateovershoot well and should be configured to provide more margin.

FIG. 3 is flow chart that shows an example of a process 300 fordetermining PID control parameters. In some implementations, process 300can be performed by the parameter controller 140 of the example system100 shown in FIG. 1.

At 310 a turbine response value is received. The turbine response valueis based on at least one first control parameter and an input value. Forexample, the feedback signal 132 is received at the parameter controller140. The feedback signal 132 provides information about an output of theturbine assembly 110, such as turbine speed, turbine load, outlettemperature, flow, current, voltage, inlet pressure, outlet pressure,extraction pressure, or vibration that is generated by the turbine 112,which is controlled by the PID controller 120 based on the inputparameter 122 and the control parameters 124.

At 320, at least one second control parameter is determined based on theturbine response value and a parameter adjustment algorithm. Forexample, the parameter controller 140 can execute the parameteradjustment algorithm 144 to determine the P gain parameter 210, the Igain parameter 220, and/or the SDR parameter 230.

The parameter adjustment algorithm may have five inputs or handles thatthe user can adjust. The user can adjust the desired speed of theresponse by configuring a “FAST_SLOW” input parameter. The user canselect P, PI, or PID control, by configuring a “P_PI_PID input”parameter. The user can select the desired allowable actuator movementlimit by configuring an “OUT_MV_LMT” input parameter. The user can alsoselect the desired allowable process movement by configuring a“PRC_MV_LMT” input parameter, and the allowable droop process movementby configuring a “DRP_MVLMT” input parameter.

In the present example, the parameter adjustment algorithm operatessubstantially synchronously with the PID controller 120, atsubstantially the same recursion rate as the PID controller 120, andwith inputs and outputs which are substantially synchronized to the PIDcontroller 120. In some implementations, this concept could also beimplemented in systems with different recursion rates among the PIDcontroller, the parameter adjustment algorithm, and the system inputsand outputs. When enabled, the parameter adjustment algorithm initiallycontrols the actuator directly, and observes the turbine response. Theactuator moves up and down, within the OUT_MV_LMT and PRC_MV_LMTparameters, based on the process response. When the process moves up,the actuator moves down, and vice versa. From the process response, thesystem gain, the system response frequency, and the relative system deadtime are observed.

The system gain is a ratio of the amount of process movement change tothe amount of actuator movement change. The system gain can becalculated by measuring the amplitude of the actuator movement,measuring the amplitude of the process movement, and dividing them. Bydefinition of a closed loop, the P value should be a fraction of theinverse of the system gain. If the P value, multiplied by the systemgain, is greater than 1 then the loop will be unstable because the loopgain will be greater than 1. The amount of process movement andfrequency of process movement is varied during the test, and the systemgain is calculated for each variation. This relative system gain is theratio of the system gain for high frequency/low amplitude changes, tothe system gain for low frequency/high amplitude changes.

The system response frequency is the frequency at which the systemresponds to actuator changes. The system frequency can be calculated bymeasuring the period of the turbine response, and inverting it. Bydefinition of a closed loop, the I value is generally configured to be afraction of the system response frequency, and the D value is generallyconfigured to be a fraction of the inverse of the system responsefrequency. If the I value exceeds the system response frequency, or theD value exceeds the inverse of the system response frequency, the systemwill be unstable, because the control will request faster movement thanthe turbine system can provide.

The system dead time is the elapsed time between an actuator movementchange from steady state until the beginning of a process movementchange. The relative system dead time is the ratio of the system deadtime, to the system response frequency.

The new P, I, and D values are calculated based on the system gain,relative system gain, system response frequency and relative system deadtime parameters, and on the FAST_SLOW input, as well as the P_PI_PIDinput. There are many tuning algorithms which use system gain and systemresponse as inputs, such as the Ziegler-Nichols algorithm. There arealso algorithms which use system gain, system response, and system deadtime as inputs, such as the Cohen-Coon algorithm. Both of thesealgorithms are referenced in multiple publications, and in variousimplementations, each algorithm can have its own comparative advantagesand disadvantages. For example, the Ziegler-Nichols and relatedalgorithms may be selected for use in systems with minimal dead time,but may not always work well for systems with significant dead time, andcan be too aggressive for some systems. In another example, theCohen-Coon and similar algorithms may be selected for use in systemswith significant dead times, but these algorithms may not always workwell for systems which are modeled by integrators, such as unloadedturbines. In some implementations, the Ziegler-Nichols algorithm, theCohen-Coon algorithm, or a combination of these and any otherappropriate algorithm for tuning P, I, and/or D gain values may be usedby the parameter controller 140.

The P value, which is calculated by the parameter controller 140, is afunction of the system gain, relative system gain, the relative systemdead time, the FAST_SLOW input, and whether the system is configured asa P, PI, or PID control (e.g., the P_PI_PID input). The P value isinversely proportional to the system gain. The calculated P value ismodified, based on the relative system gain, relative system dead timeand on whether the control is configured to be a P, PI, or PID control.High relative system gains and high relative system dead times woulddecrease the P value. In implementations in which long relative deadtimes are expected, an algorithm similar to the Cohen-Coon algorithm maybe used, while other systems may use an algorithm similar to theZiegler-Nichols algorithm. The FAST_SLOW input provides the user with again adjustment for the P value. In various implementations, differentequations can be used for a PID control configuration, a PI controlconfiguration, and a P control configuration. PID control configurationswill have relatively higher P and I terms than a PI controlconfiguration, which will have a relatively higher P term than aproportional (P) control configuration.

The I and the D values, which are calculated by the parameter controller140, are a function of the measured system response frequency, therelative system gain, the relative system dead time, the FAST_SLOWinput, and on whether the system is configured as a P, PI, or PIDcontrol (e.g., the P_PI_PID input). The calculated I and D values aremodified, based on the relative system gain, relative system dead time,the FAST_SLOW input, and on whether the control is configured to be a P,PI, or PID control. High relative system gains and high relative systemdead times would increase the calculated I value and decrease thecalculated D value. In some implementations in which relatively longdead times are expected, an algorithm similar to the Cohen-Coonalgorithm can be used, while other systems can use an algorithm similarto the Ziegler-Nichols algorithm. As is typically seen in publishedliterature, a PID control configuration will have relatively higher gainvalues for the P and I terms than are used a PI control configuration.

When the PID controller 120 is configured with a PI controlconfiguration, the recommended D is set to 0, and the PID controller 120is configured as a PI control. When the system is PID as a proportionalcontrol, the recommended D and I are set to 0, and the PID controller120 is configured as a proportional control. As seen in the parallel PIDequation above, the effect of I and D are also a function of P.

After calculating the new values, the parameter adjustment algorithm 144performs a step response of the PID controller 120, using newlycalculated P, I, and D values, and monitors the response. The P, I, andD values are modified as necessary, based on the system gain, relativesystem gain, system response, and relative system dead time, asdescribed above.

At 330 the at least one second control parameter is provided. Forexample, the parameter controller 140 can provide the collection ofcontrol parameters 142 to the PID controller 120 for use as thecollection of control parameters 124.

FIG. 4 is flow chart that shows an example of a process 400 forcontrolling industrial turbines. For example the process 400 can beperformed by the example system 100 shown in FIG. 1.

At 410 a PID controller is provided. The PID controller is configured toperform a control algorithm based on at least one first controlparameter. For example, the PID controller 120 is provided, and the PIDcontroller 120 performs a control algorithm to control the turbineassembly 110. In some implementations, the first input value can be aturbine speed, an outlet temperature, an inlet pressure, and/or andextraction pressure.

At 420, a parameter controller is provided. The parameter controller isconfigured to perform a parameter adjustment algorithm. For example, theparameter controller 140 is configured to perform the parameteradjustment algorithm 144.

At 430 a turbine is provided. The turbine includes a turbine outputsensor in communication with the PID controller and the parametercontroller. For example, the turbine 112 has the sensor 130 assembled toit.

At 440 at least one first control parameter and a first input value areprovided to the PID controller. For example, the input parameter 122 andthe collection of parameters 124 are provided to the PID controller 120.In some implementations, the at least one first control parameter can bethe P gain parameter 210, the I gain parameter 220, and/or the SDRparameter 230.

At 450 the PID controller controls the turbine based on the at least onefirst control parameter and the first input value. For example, the PIDcontroller 120 controls the controllable inputs 114, based on the inputparameter 122 and the collection of parameters 124, to control theturbine 112.

At 460 the parameter controller receives a turbine response valueprovided by the turbine output sensor. For example, the parametercontroller 140 receives the feedback signal 132. The feedback signal 132can be processed to determine one or more values that can describe theresponse of the turbine 112 to the input parameter 122 and thecollection of control parameters 124.

At 470, the parameter controller determines at least one second controlparameter based on the turbine response value and the parameteradjustment algorithm. For example, the parameter controller 140determines the collection of control parameters 142. In someimplementations, the collection of control parameters 142 can bedifferent from the collection of control parameters 124. In someimplementations, the at least one second control parameter can be the Pgain parameter 210, the I gain parameter 220, and/or the SDR parameter230.

At 480, the at least one second control parameter is provided to the PIDcontroller from the parameter controller. For example, the collection ofcontrol parameters 142 can be provided to the PID controller 120 for useas the collection of control parameters 124.

At 490 the turbine is controlled by the PID controller based on at leastone second control parameter and a second input value. For example, thecollection of control parameters 142 can be used by the PID controller120 as the collection of control parameters 124 for controlling theturbine assembly 110. In some implementations, the second input valuecan be a turbine speed, an outlet temperature, an inlet pressure, and/orand extraction pressure.

FIG. 5 is flow chart that shows another example of a process 500 fordetermining PID control parameters. In some implementations, the process500 can be performed by the industrial turbine control system 100.

At 510, the system is allowed to settle in to a substantially steadystate of operation relative to the input parameter 122. At 520, theoutput of the system is measured using an algorithm that is configuredfor the type of turbine in use as the turbine 112. For example, thealgorithm may be configured differently for a steam turbine, a liquidfueled turbine (e.g., an aircraft turbine), or a gas fueled turbine(e.g., natural gas turbine). In some implementations, the algorithm maybe configured differently for different types of control. For example,the algorithm may be configured differently for speed control, loadcontrol, temperature control, or for combinations of these or any othercontrollable outputs of the turbine 112.

At 530, the parameter adjustment algorithm 144 is performed to calculatethe collection of control parameters 142 based on the measured systemparameters and a desired response input 540. At 550 the calculatedcollection of control parameters 142 is used in conjunction with a testinput 560 to test the collection of control parameters 142 and trigger afurther adjustment of the collection of control parameters 142, ifneeded.

FIG. 6 is flow chart that shows another example of a process 600 fordetermining PID control parameters. In some implementations, the process600 can be performed by the industrial turbine control system 100. Insome implementations, the process 600 can be a more detailed embodimentof the process 500 of FIG. 5.

A process input 602 is provided to a turbine control process 604. Theturbine control process 604 controls a turbine to provide an actuatoroutput 606. For example, the process input 602 can be a speed parameter,and the turbine control process 604 can be a speed control process forthe turbine by actuating a fuel or steam valve as the actuator output606.

At 610, the initial signals are measured. The initial signals areprovided by a feedback sensor that can be used to measure one or moreoutputs of the turbine. For example, the sensor 130 can provide thefeedback signal 132, and the feedback signal 132 can be processed todetermine the initial control state.

At 612 a determination is made. If the movement exceeds the userselected movement limit, then a normal PID loop is performed at 614. Forexample, the parameter controller 140 can determine that the turbine 112is not operating at steady state, and in response the parametercontroller 140 can allow the PID controller 120 to continue to controlthe turbine assembly 110.

If the system movement is acceptable, at 616 another determination ismade. If adaptive control is not enabled, a normal PID loop is performedat 614. If adaptive control is enabled, the system response is tested at650. For example, the parameter controller 140 can provide a desiredoutput setting as the input parameter 122 to the PID controller 120.

At 652 a determination is made. If an insufficient response is receivedfrom the turbine in response to the input parameter, at 654 theexcitation (e.g., input parameter 122) is adjusted. If a sufficientresponse is received from the turbine in response to the inputparameter, another determination is made at 660.

If at 660, an insufficient amount of data about the response of theturbine to the input parameter has been received, the system responsecontinues to be tested at 650. If at 660, enough data about the responseof the turbine to the input parameter has been received, at 670 the Pgain, the I gain, and the SDR gain are calculated based on a desiredresponse 672. At 680, the calculated P, I, and SDR gains are tested. Forexample, the parameter controller 140 can provide the control parameters142 to the PID controller 120 for use as the control parameters 124, andthe response of the turbine assembly 110 can be evaluated to test theperformance of the calculated P, I, and SDR gains for the inputparameter 122.

FIG. 7 is a chart 700 showing an example result of tuning an industrialturbine PID controller controlling a steam turbine off line, pulling avacuum, with an initially underdamped response. The steam turbine systemis modeled with a 0.5 Hz actuator with 20 mS dead time, a controlrecursion rate of 5 mS, and a turbine with 0.001% damping, running at3600 RPM, with no load. The desired process movement limit was 0.5%, andthe actuator movement was limited to 0.025%. The initial P term was setto 0.0001, the initial I term was set to 0.0001, and SDR was set to 100,denoting a PI controller configuration. The chart 700 represents time(in seconds) along the x-axis, and the y-axis represents the measuredprocess output parameter, e.g., rotational speed in RPMs in thisexample. The chart 700 includes a collection of reference input values702 and a collection of response output values 704 for an industrialturbine, such as the turbine 112 of the example system shown in FIG. 1.During a time period 710, from about the 50 s mark to about the 100 smark, the turbine is excited while operating under an initial P gain, Igain, and D gain. The response output values 704 show that the system ismarginally stable under the initial collection of gain settings, andexhibits traits indicative of initial gain settings that may be toohigh.

During a time period 720, from about the 100 s mark to about the 157 smark, the turbine is perturbed, for example by the parameter controller140. In some implementations, the system gain and relative system gaincan be determined by measuring the ratio of process movement, to outputdemand movement. The system response frequency can be determined bymeasuring the frequency of the process response. The relative systemdead time can be determined by measuring the delay between the movementof the output demand, and the process movement. As seen by the systemsettings above, and the plots, the system dead time is minimal. Theseparameters can be used to determine updated P, I, and D gain values, asexplained above. The updated P, I, and SDR gain values, are 0.0015,0.21, and 6.85, respectively. The process for determining the D gainvalue is selected based on the SDR gain value. If SDR>1, thenD=1/[(SDR)(I)]. If SDR<1, then D=SDR/I. If [(SDR>=100) or (SDR<=0.01)],then the control is a PI control and D is set to 0. In the currentexample, the corresponding D value would be 0.69. Those updated P, I,and D gains are then provided to the PID controller for use in thecontrol of the turbine.

During a time period 730, from about the 157 s mark onward, the turbineis controlled using the updated P, I, and D gains. The response of thesystem during the time period 730 (e.g., after adjustment by theparameter controller 140) is more stable than the system's responseduring the time period 710 (e.g., prior to adjustment by the parametercontroller 140).

FIG. 8 is a chart 800 showing an example result of tuning an industrialturbine PID controller controlling a steam turbine, off line, pulling avacuum, with an initially overdamped response. Again, the steam turbinesystem is modeled with a 0.5 Hz actuator with 20 mS dead time, a controlrecursion rate of 5 mS, and a turbine with 0.001% damping, running at3600 RPM, with no load. The desired process movement limit was 0.5%, andthe actuator movement was limited to 0.025%. The initial P term was setto 0.01, the initial I term was set to 0.01, and SDR was set to 100,denoting a PI controller configuration. The chart 800 represents time(in seconds) along the x-axis, and y-axis represents the measuredprocess output parameter, e.g., rotational speed in RPMs in thisexample. The chart 800 includes a collection of reference input values802 and a collection of response output values 804 for an industrialturbine, such as the turbine 112 of the example system shown in FIG. 1.During a time period 810, from about the 50 s mark to about the 100 smark, the turbine is excited while operating under an initial P gain, Igain, and D gain. The response output values 804 show that the system isoverdamped (e.g., sluggish response) and did not reach the set pointduring the given time period 810. Such behavior can be indicative ofinitial gain settings that may be too low.

During a time period 820, from about the 100 s mark to about the 157 smark, the turbine is perturbed, for example by the parameter controller140, and the response of the turbine is processed. In someimplementations, the system gain and relative system gain can bedetermined by measuring the ratio of process movement, to output demandmovement. The system response frequency can be determined by measuringthe frequency of the process response. The relative system dead time canbe determined by measuring the delay between the movement of the outputdemand, and the process movement. These parameters are used to determineupdated P, I, and D gain values, as explained above. Those updated P, I,and D gains are then provided to the PID controller for use in thecontrol of the turbine.

During a time period 830, from about the 157 s mark onward, the turbineis controlled using the updated P, I, and SDR gains, of 0.0015, 0.21,and 6.85, respectively. The response of the system during the timeperiod 830 (e.g., after adjustment by the parameter controller 140) ismore responsive than the system's response during the time period 810(e.g., prior to adjustment by the parameter controller 140). Note thatFIGS. 7 and 8 show repeatable P, I, and D terms, as well as repeatableresponses for each of the tuning sequences with good performance andgood margin (fast response, minimal ringing), regardless of the initialvalues used by the PID controller 120 and the initial response of thePID controller 120 and the turbine assembly 110. The parametercontroller 140 can work as well with a system that is initiallysluggish, overdamped, and unresponsive, as with a system which ismarginally stable and ringing.

FIG. 9 is a schematic diagram that shows an example of anotherindustrial turbine control system 900. A turbine assembly 910 includes aturbine 912, a controllable low pressure (LP) input 914 a and acontrollable high pressure (HP) input 914 b for controlling the flow ofa collection of one or more fluid or steam supplies to or from theturbine 912. By controllably adjusting the LP input 914 a and the HPinput 914 b to control the flows of the steam/fluid supplies to/from theturbine 912, the rotational speed, load, acceleration, deceleration, andother performance parameters of the turbine 912 can be controllablyadjusted. In some embodiments, the turbine assembly 910 can be theturbine assembly 110 of FIG. 1. In some embodiments, the LP input 914 aand the HP input 914 b can be the controllable inputs 114 of FIG. 1.

In the example system shown in FIG. 9, the LP and HP inputs 914 a-914 bare adjusted by a turbine controller 920. The turbine controller 920adjusts the LP an HP inputs 914 a-914 b based on a collection of inputparameters 922 (e.g., desired turbine speed, desired pressure), one ormore feedback signals 932 provided by one or more sensors 930 configuredto sense the speed and pressure of the turbine 912, a collection ofoutputs 918, and combinations of these or other appropriate operationalparameters of the turbine 912, and a collection of control parameters ina closed-loop feedback control system. In some embodiments, the sensors930 can be the sensor 130 of FIG. 1. The turbine controller 920 and itsoperations will be discussed further in the descriptions of FIGS. 10-22.

FIG. 10 is a block diagram 1000 of the example turbine controller 920 ofFIG. 9. The turbine controller 920 includes a speed (S) PID controller1002 and an extraction pressure (P) PID controller 1004. The S PIDcontroller 1002 receives an S process input value 1006 (e.g., a userprovided desired speed value), and the P PID controller 1004 receives aP process input value 1008 (e.g., a user provided desired extractionpressure value). In some embodiments, the S PID controller 1002 and theP PID controller 1004 can each be examples of the PID controller 120 ofFIG. 1.

The turbine controller 920 includes a ratio controller 1010. The ratiocontroller 1010 provides a high pressure (HP) actuator output 1020 and alow pressure (LP) actuator output 1022. In operation, the LP actuatoroutput 1022 is provided to an LP actuator such as the LP input 914 a ofFIG. 9 (e.g., to control a valve on the low pressure side of the turbine912). In operation, the HP actuator output 1020 is provided to an HPactuator such as the HP input 914 b of FIG. 9 (e.g., to control a valveon the high pressure side of the turbine 912).

The turbine controller 920 is also configured to receive a tuning enableinput 1009. An adaptive control selector 1012 is configured to alter theoperation of the turbine controller 920 based on the state of the tuningenable input 1009. Referring now to FIG. 11, a flow diagram 1100 showsan example process for selecting an operational mode of the exampleturbine controller 920 of FIG. 9. In the example flow diagram 1100, theturbine controller 920 receives a collection of process inputs 1102,such as the S input 1002, the P input 1004, and the tuning enable input1009 of FIG. 10, and provides the HP actuator output 1020 and the LPactuator output 1022.

The adaptive control selector 1012 alters the operation of the turbinecontroller 920 based on the process inputs 1102 (e.g., the tuning enableinput 1009 of FIG. 10) to cause the turbine controller 920 to operate ineither a normal PID operation mode 1110 or an automatic PID tuning mode1112.

FIG. 12 is a block diagram 1200 of the example turbine controller 920 ofFIG. 9 in the normal PID operation mode 1110 of FIG. 11. Under normaloperation (e.g., the tuning enable input 1009 is off), the HP actuatoroutput 1020 and the LP actuator output 1022 are based on the outputvalues of the S PID 1002 and the P PID 1004 received by the ratiocontroller 1010. The ratio controller 1010 modifies the output values ofthe PIDs 1002-1004 using a scaler 1202 and a scaler 1204.

The turbine controller 920 is an example of a Multi-Input Multi-Output(MIMO) control system (e.g., a system with more than one control inputand more than one control output). In some implementations, one of theactuator outputs 1020, 1022 can affect both of the control inputs 1006,1008, and the system is said to have “interaction”. Interaction can bereduced by use of a steam map, or ratio-limiter. Ratio refers toapplying scaling terms to the demands of each of the control loops, suchthat each control loop controls both valves with minimal effect on theother control loop. Limiting refers to the case in which a controlledoutput (e.g., the LP input 914 a and/or the HP input 914 b) reaches itscontrolling limit. The calculation of the ratio gains, which are alsoreferred to as “K” coefficients, is determined by converting aperformance curve for a turbine into a turbine control operationalenvelope. In some examples, the performance curve may be provided by themanufacturer of the turbine, and from this information a turbine controloperational envelope can be determined. In some examples, such anoperational envelope may be referred to as a steam map. An example of asteam map that can be used to determine K coefficients is discussed inthe description of FIG. 23.

In the present example, ratio gains are referred to as “K” coefficients.The K coefficients are combined with the classical PID outputs for thespeed (S) PID controller 1002 and the extraction pressure (P) PIDcontroller 1004 to provide the components for the scaler 1202 and thescaler 1204 calculations for the valve demands.

In the illustrated example, the scaler 1202 provides the HP actuatoroutput 1020 based on the equation:

HP=K ₁ S+K ₂ P+K ₃

The scaler 1204 provides the LP actuator output 1022 based on theequation:

LP=K ₄ S+K ₅ P+K ₆

FIG. 13 is a flow diagram of an example process 1300 for tuning multipleactuator controllers. In some implementations, the process 1300 can beused by the example turbine controller 920 to tune the example turbinesystem 900 of FIG. 9. When automatic tuning is turned on (e.g., thetuning enable input 1009 of FIG. 10 is on), the example turbinecontroller 920 of FIG. 9 alters the operations of the S PID controller1002, the P PID controller 1004, and the ratio controller 1010 to tunethe operational parameters of the S PID controller 1002 and the P PIDcontroller 1004.

At 1302, an adaptive control input is received. For example, the turbinecontroller 920 can receive the tuning enable input 1009 to put theturbine controller 920 into an automatic tuning operational mode.

At 1304 the S PID controller 1002 is tuned while the P PID controller1004 output is overridden with a fixed output value. For example, the SPID controller 1002 can be exercised through a range of set points toexamine the performance of the example turbine system 900 substantiallyindependent of the influence of the P PID controller 1004, the output ofwhich is otherwise interactive with that of the S PID controller 1002.The P, I, and SDR parameters of the S PID controller 1002 are thenupdated based on the observed performance of the turbine system 920.

At 1306 the P PID controller 1004 is tuned while the s PID controller1002 output is overridden with a fixed output value. For example, the PPID controller 1004 can be exercised through a range of set points toexamine the performance of the example turbine system 900 substantiallyindependent of the influence of the S PID controller 1002, the output ofwhich is otherwise interactive with that of the P PID controller 1004.The P, I, and SDR parameters of the P PID controller 1004 are thenupdated based on the observed performance of the turbine system 920.

At 1308 the S PID controller 1002 is tuned while the P PID controller1004 is allowed to operate normally. For example, the S PID controller1002 can be exercised through a range of set points to examine theperformance of the example turbine system 900 as the influence of the PPID controller 1004 is allowed to interact with the output of the S PIDcontroller 1002. The P, I, and SDR parameters of the S PID controller1002 are then updated based on the observed performance of the turbinesystem 920.

At 1310 the P PID controller 1004 is tuned while the S PID controller1002 is allowed to operate normally. For example, the P PID controller1004 can be exercised through a range of set points to examine theperformance of the example turbine system 900 as the influence of the SPID controller 1002 is allowed to interact with the output of the P PIDcontroller 1004. The P, I, and SDR parameters of the P PID controller1004 are then updated based on the observed performance of the turbinesystem 920.

At 1312, the turbine controller 920 uses the determined values of P, I,and SDR for each of the S PID controller 1002 and the P PID controller1004 to operate in a normal operational mode (e.g., both PID controllers1002, 1004 operating normally).

FIG. 14 is a block diagram of the example turbine controller 920 of FIG.12 in a tuning mode configuration 1400. In some implementations, theconfiguration 1400 can be used by the turbine controller 920 to performstep 1304 of the example process 1300 of FIG. 13.

In the illustrated example, the ratio controller 1010 receives an Soutput from the S PID controller 1002. The output of the P PIDcontroller 1004, however, is intercepted, and is replaced by a simulatedP output 1402. In some implementations, the simulated P output 1402 canbe a constant value. In some implementations, the simulated P output1402 can be a filtered, sampled value of the P output of the P PIDcontroller 1004. The HP actuator output 1020 and the LP actuator output1022 are determined based on the actual S output of the S PID controller1002 and on the simulated P output 1402.

FIG. 15 is a flow diagram of an example process stage 1500 for tuningmultiple actuator controllers. In some implementations, the processstage 1500 can be the step 1304 of the example process 1300 of FIG. 13.In some implementations, the process stage 1500 may be performed by theexample configuration 1400 of FIG. 14.

In general, the process stage 1500 includes two sub processes. A subprocess 1510 adjusts the S PID controller 1002 of FIG. 10 through arange of values as part of an automatic tuning process for the S PIDcontroller 1002. A sub process 1550 monitors the inputs of both the SPID controller 1002 and the P PID controller 1004. In someimplementations, the sub processes 1510 and 1550 can run substantiallyin parallel.

In the sub process 1510, at step 1512, the system response of the S PIDcontroller 1002 is tested by providing predetermined excitation values.If at step 1514 the turbine controller 920 determines that an incorrectexcitation is being provided to the S PID controller 1002, then at step1516 the excitation level is adjusted (e.g., higher or lower). If atstep 1514, the turbine controller 920 determines that a correct level ofexcitation is being provided to the S PID controller 1002, then anotherdetermination is made at step 1518.

At step 1518, if the turbine controller 920 determines that not enoughdata has been collected (e.g., turbine system response data), then the SPID controller 1002 is stimulated again at step 1512. If the turbinecontroller 920 determines that enough data has been collected, then atstep 1520 new P, I, and SDR values are determined for the S PIDcontroller 1002 based on a desired response 1522. In someimplementations, the new P, I, and SDR values can be determined usingthe example process 300 of FIG. 3, the example process 400 of FIG. 4,the example process 500 of FIG. 5, the example process 600 of FIG. 6,and/or the example process 1300 of FIG. 13.

The sub process 1550 includes a step 1552 at which the inputs to the SPID controller 1002 and the P PID controller 1004 are monitored. At1554, if there is more than a predetermined threshold amount of movementon the PID controllers' inputs based on an allowed change input value1556, then at 1590 tuning is stopped and the S PID controller 1002 andthe P PID controller 1004 are allowed to run normally. If at 1554, theamount of movement on the PID controllers' inputs does not exceed thepredetermined threshold amount based on the input value 1556, then theprocess stage 1500 is allowed to complete.

FIG. 16 is a block diagram of the example turbine controller 920 of FIG.12 in another tuning mode configuration 1600. In some implementations,the configuration 1600 can be used by the turbine controller 920 toperform step 1306 of the example process 1300 of FIG. 13.

In the illustrated example, the ratio controller 1010 receives a Poutput from the P PID controller 1004. The output of the S PIDcontroller 1002, however, is intercepted, and is replaced by a simulatedS output 1602. In some implementations, the simulated S output 1602 canbe a constant value. In some implementations, the simulated S output1602 can be a filtered, sampled value of the S output of the S PIDcontroller 1002. The HP actuator output 1020 and the LP actuator output1022 are determined based on the actual P output of the P PID controller1004 and on the simulated S output 1602.

FIG. 17 is a flow diagram of an example process stage 1700 for tuningmultiple actuator controllers. In some implementations, the processstage 1700 can be the step 1306 of the example process 1300 of FIG. 13.In some implementations, the process stage 1700 may be performed by theexample configuration 1600 of FIG. 16.

In general, the process stage 1700 includes two sub processes. A subprocess 1710 adjusts the P PID controller 1004 of FIG. 10 through arange of values as part of an automatic tuning process for the P PIDcontroller 1004. A sub process 1750 monitors the inputs of both the SPID controller 1002 and the P PID controller 1004. In someimplementations, the sub processes 1710 and 1750 can run substantiallyin parallel.

In the sub process 1710, at step 1712, the system response of the P PIDcontroller 1004 is tested by providing predetermined excitation values.If at step 1714 the turbine controller 920 determines that an incorrectexcitation is being provided to the P PID controller 1004, then at step1716 the excitation level is adjusted (e.g., higher or lower). If atstep 1714, the turbine controller 920 determines that a correct level ofexcitation is being provided to the P PID controller 1004, then anotherdetermination is made at step 1718.

At step 1718, if the turbine controller 920 determines that not enoughdata has been collected (e.g., turbine system response data), then the PPID controller 1004 is stimulated again at step 1712. If the turbinecontroller 920 determines that enough data has been collected, then atstep 1720 new P, I, and SDR values are determined for the P PIDcontroller 1004 based on a desired response 1722. In someimplementations, the new P, I, and SDR values can be determined usingthe example process 300 of FIG. 3, the example process 400 of FIG. 4,the example process 500 of FIG. 5, the example process 600 of FIG. 6,and/or the example process 1300 of FIG. 13.

The sub process 1750 includes a step 1752 at which the inputs to the SPID controller 1002 and the P PID controller 1004 are monitored. At1754, if there is more than a predetermined threshold amount of movementon the PID controllers' inputs based on an allowed change input value1756, then at 1790 tuning is stopped and the S PID controller 1002 andthe P PID controller 1004 are allowed to run normally. If at 1754, theamount of movement on the PID controllers' inputs does not exceed thepredetermined threshold amount based on the input value 1756, then theprocess stage 1700 is allowed to complete.

FIG. 18 is a flow diagram of an example process stage 1800 for tuningmultiple actuator controllers. In some implementations, the processstage 1800 can be the step 1308 of the example process 1300 of FIG. 13.In some implementations, the process stage 1800 may be performed by theexample configuration 1200 of FIG. 12.

In general, the process stage 1800 includes two sub processes. A subprocess 1810 adjusts the S PID controller 1002 of FIG. 10 through arange of values as part of an automatic tuning process for the S PIDcontroller 1002. A sub process 1850 monitors the inputs of the P PIDcontroller 1004. In some implementations, the sub processes 1810 and1850 can run substantially in parallel.

In the sub process 1810, at step 1812, the system response of the S PIDcontroller 1002 is tested by stepping the set point of the S PIDcontroller 1002 up and observing the response of the turbine system 900.At step 1814, the system response of the S PID controller 1002 is testedby stepping the set point of the S PID controller 1002 down andobserving the response of the turbine system 900. For example, steps1812 and 1814 may exercise the S PID controller 1002 through apredetermined range of set points both above and below an expected setpoint.

At step 1818, if the turbine controller 920 analyzes the turbine system900 response data produced during steps 1812 and 1814. At step 1820 newP, I, and SDR values are determined for the S PID controller 1002 basedon a desired response 1822. In some implementations, the new P, I, andSDR values can be determined using the example process 300 of FIG. 3,the example process 400 of FIG. 4, the example process 500 of FIG. 5,the example process 600 of FIG. 6, and/or the example process 1300 ofFIG. 13.

The sub process 1850 includes a step 1852 at which the inputs to the PPID controller 1004 are monitored. At 1854, if there is more than apredetermined threshold amount of movement on the PID controller's inputbased on an allowed change input value 1856, then at 1890 tuning isstopped and the S PID controller 1002 and the P PID controller 1004 areallowed to run normally. If at 1854, the amount of movement on the PIDcontroller's inputs does not exceed the predetermined threshold amountbased on the input value 1856, then the P PID controller 1004 is runwith a normal set point.

FIG. 19 is a flow diagram of an example process stage 1900 for tuningmultiple actuator controllers. In some implementations, the processstage 1900 can be the step 1310 of the example process 1300 of FIG. 13.In some implementations, the process stage 1900 may be performed by theexample configuration 1200 of FIG. 12.

In general, the process stage 1900 includes two sub processes. A subprocess 1910 adjusts the P PID controller 1004 of FIG. 10 through arange of values as part of an automatic tuning process for the P PIDcontroller 1004. A sub process 1950 monitors the inputs of the S PIDcontroller 1002. In some implementations, the sub processes 1910 and1950 can run substantially in parallel.

In the sub process 1910, at step 1912, the system response of the P PIDcontroller 1004 is tested by stepping the set point of the P PIDcontroller 1004 up and observing the response of the turbine system 900.At step 1914, the system response of the P PID controller 1004 is testedby stepping the set point of the P PID controller 1004 down andobserving the response of the turbine system 900. For example, steps1912 and 1914 may exercise the P PID controller 1004 through apredetermined range of set points both above and below an expected setpoint.

At step 1919, if the turbine controller 920 analyzes the turbine system900 response data produced during steps 1912 and 1914. At step 1920 newP, I, and SDR values are determined for the P PID controller 1004 basedon a desired response 1922. In some implementations, the new P, I, andSDR values can be determined using the example process 300 of FIG. 3,the example process 400 of FIG. 4, the example process 500 of FIG. 5,the example process 600 of FIG. 6, and/or the example process 1300 ofFIG. 13.

The sub process 1950 includes a step 1952 at which the inputs to the SPID controller 1002 are monitored. At 1954, if there is more than apredetermined threshold amount of movement on the PID controller's inputbased on an allowed change input value 1956, then at 1990 tuning isstopped and the S PID controller 1002 and the P PID controller 1004 areallowed to run normally. If at 1954, the amount of movement on the PIDcontroller's inputs does not exceed the predetermined threshold amountbased on the input value 1956, then the S PID controller 1002 is runwith a normal set point.

FIG. 20 is a flow diagram of another example process stage 2000 fortuning multiple actuator controllers. In some implementations, theprocess stage 2000 can be the step 1312 of the example process 1300 ofFIG. 13. In some implementations, the process stage 2000 may beperformed by the example configuration 1200 of FIG. 12.

In general, the process stage 2000 includes two sub processes. A subprocess 2010 monitors the S PID controller 1002 of FIG. 10 as part of anautomatic tuning process for the S PID controller 1002. A sub process2050 monitors the P PID controller 1004 of FIG. 10 as part of anautomatic tuning process for the P PID controller 1004. In someimplementations, the sub processes 2010 and 2050 can run substantiallyin parallel.

The sub process 2010 includes a step 2012 at which the inputs to the SPID controller 1002 are monitored. At 2014, if there is more than apredetermined threshold amount of movement on the PID controller's inputbased on an allowed change input value 2016 and/or the amount of inputnoise, then at 2090 tuning is stopped and the S PID controller 1002 andthe P PID controller 1004 are allowed to run normally. If at 2014, theamount of movement on the PID controller's inputs does not exceed thepredetermined threshold amount based on the input value 2016, thenanother determination is made.

At 2018, if the tuning process is not finished based on an input 2020(e.g., a user input), then tuning continues at step 2012. If, at 2018,the tuning process is finished based on the input 2020, then anotherdetermination is made.

At 2022, if the P, I, and SDR values determined by the previous tuningsteps are not to be saved based on an input 2024 (e.g., a user input),then at 2090 tuning is stopped and the S PID controller 1002 and the PPID controller 1004 are allowed to run normally, with the original P, I,and SDR values. If, at 2022, the P, I, and SDR values determined by theprevious tuning steps are to be saved based on the input 2024, then at2026 the S PID 1002 is run with a normal set point with the newlycalculated P, I, and SDR values.

The sub process 2050 includes a step 2052 at which the inputs to the PPID controller 1004 are monitored. At 2054, if there is more than apredetermined threshold amount of movement on the PID controller's inputbased on an allowed change input value 2056, then at 2092 tuning isstopped and the S PID controller 1002 and the P PID controller 1004 areallowed to run normally, with the original P, I, and SDR values. If at2054, the amount of movement on the PID controller's inputs does notexceed the predetermined threshold amount based on the input value 2056,then another determination is made.

At 2058, if the tuning process is not finished based on an input 2060(e.g., a user input), then tuning continues at step 2052. If, at 2058,the tuning process is finished based on the input 2060, then anotherdetermination is made.

At 2062, if the P, I, and SDR values determined by the previous tuningsteps are not to be saved based on an input 2064 (e.g., a user input),then at 2092 tuning is stopped and the S PID controller 1002 and the PPID controller 1004 are allowed to run normally, with the original P, I,and SDR values. If, at 2062, the P, I, and SDR values determined by theprevious tuning steps are to be saved based on the input 2064, then at2066 the P PID 1004 is run with a normal set point with the newlycalculated P, I, and SDR values.

FIGS. 21A and 21B are flow diagrams of another example process 2100 fortuning multiple actuator controllers. In some implementations, theprocess 2100 can be used by the example turbine controller 920 to tunethe example turbine system 900 of FIG. 9.

At step 2102 one or more turbine response values are received at a ratiocontroller. In some embodiments, the ratio controller can be the exampleratio controller 1010 of FIG. 10. The turbine response values are basedon a first process output value (S_(out)) of a first actuatorcontroller, the first process output value being based on a firstprocess input value (S_(in)) and at least one first control parameterselected from a group including a proportional gain value (P), anintegral gain value (I), and a derivative gain value (SDR), wherein thefirst actuator controller includes a first parameter controller, and asecond process output value (P_(out)) of a second actuator controller,the second process output value based on a second process input value(P_(in)) and at least one second control parameter selected from thegroup, wherein the second actuator controller includes a secondparameter controller. For example, the first process output value can bethe output of the S PID controller 1002, and the second process outputvalue can be the output of the P PID controller 1004.

At 2104, the ratio controller provides the first actuator controllerwith the first process input value as a predetermined first constant setpoint value, and at 2106 the ratio controller varies the second processinput value provided to the second actuator controller to a plurality ofpredetermined first set point values. For example, the set point of theS PID controller 1002 can be held constant while the set point of the PPID controller 1004 is varied through a range of set point values. Insome implementations, steps 2104 and 2106 may be performed with theturbine controller 920 in the example configuration 1400 of FIG. 14.

At 2108 the second parameter controller receives one or more firstupdated turbine response values as the turbine response values for oneor more of the first set point values. At 2110 the second parametercontroller determines at least one third control parameter selected fromthe group based on the turbine response values, and at 2112, the secondparameter controller provides the third control parameter as the secondcontrol parameter to the second actuator controller. For example, the PPID controller 1004 can determine new P, I, and/or SDR values for itselfbased on the example process 400 of FIG. 4. In another example, theratio controller 1010 or another controller can determine the valuesbased on the example process 400.

As shown in FIG. 21B, at 2114, the ratio controller provides the secondactuator controller with the second process input value as apredetermined second constant set point value, and at 2116 the ratiocontroller varies the first process input value provided to the firstactuator controller to a plurality of predetermined second set pointvalues. For example, the set point of the P PID controller 1004 can beheld constant while the set point of the S PID controller 1002 is variedthrough a range of set point values. In some implementations, steps 2114and 2116 may be performed by the turbine controller 920 in the exampleconfiguration 1400 of FIG. 14.

At 2118 the first parameter controller receives one or more secondupdated turbine response values as the turbine response values for oneor more of the second set point values. At 2120 the first parametercontroller determines at least one fourth control parameter selectedfrom the group based on the turbine response values, and at 2122, thefirst parameter controller provides the fourth control parameter as thefirst control parameter to the first actuator controller. For example,the S PID controller 1002 can determine new P, I, and/or SDR values foritself based on the example process 400 of FIG. 4. In another example,the ratio controller 1010 or another controller can determine the valuesbased on the example process 400.

In some implementations, the process 2100 can also include controlling,by the first parameter controller and the second parameter controller,the turbine based on the first process output value and the secondprocess output value. For example, the S PID controller 1002 and the PPID controller 1004 can control the turbine system 900 using the updatedP, I, and SDR values.

In some implementations, the process 2100 can also include determining afirst control output value (HP) based on the first process output value(S_(out)), the second process output value (P_(out)), and the ratioparameters (K_(x)), determining a second control output value (LP) basedon the first process output value (S_(out)), the second process outputvalue (P_(out)), and the ratio parameters (Kx), and controlling, by theratio controller, the turbine based on the first control output valueand the second control output value. In some implementations the one ormore ratio parameters (Kx) can include a collection of ratio parametersK₁, K₂, K₃, K₄, K₅, and K₆, the first control output (HP) can be givenby the equation HP=K₁S_(out)+K₂P_(out)+K₃, and the second control output(LP) can be given by the equation LP=K₄S_(out)+K₅P_(out)+K₆. Forexample, the example ratio controller 1010 of FIG. 10 can modify theoutput values of the PIDs 1002 and 1004 using the example scaler 1202and the example scaler 1204 of FIG. 12 based on “K” coefficients.

In some implementations of the process 2100, the first parametercontroller can control a first component of the turbine effecting theturbine response values, and the second parameter controller can controla second component of the turbine effecting the turbine response values.For example, the example S PID controller 1002 of FIG. 10 can control aLP actuator through the LP actuator input 914 a, and the example P PIDcontroller 1004 of FIG. 10 can control a HP actuator through the HPactuator input 914 b to control the performance of the turbine 912.

While the preceding discussion has described systems and processes withcertain quantities and types of controllers (e.g., S PID controller1002, P PID controller 1004), input values (e.g., S and P), intermediatevalues (e.g., K_(x), HP, LP), controlled parameters (e.g., speed,acceleration, pressure, flow, inlet/outlet configuration,extraction/admission, exhaust), and output values (e.g., the feedbacksignal 932), other quantities and types of values may be used. Forexample, three or more PID controllers may be used, in which the inputto two of the PID controllers can be held substantially constant whilethe third PID controller is exercised through a range of values as partof an extension of the example process 2100 of FIGS. 21A-21B. In anotherexample, any appropriate number of K coefficients may be used by theratio controller 1010 to modify a collection of PID controller outputs,and/or may provide any appropriate number of scaled output values to acorresponding number of the controllable inputs 114 of FIG. 1.

FIG. 22 is a schematic diagram of an example of a generic computersystem 2200. The system 2200 can be used for the operations described inassociation with the process 300 according to one implementation. Forexample, the system 2200 may be included in either or all of theparameter controller 140 of FIG. 1, the PID controller 120, the turbinecontroller 920 of FIG. 9, the S PID controller 1002 of FIG. 10, the PPID controller 1004, and/or the ratio controller 1010.

The system 2200 includes a processor 2210, a memory 2220, a storagedevice 2230, and an input/output device 2240. Each of the components2210, 2220, 2230, and 2240 are interconnected using a system bus 2250.The processor 2210 is capable of processing instructions for executionwithin the system 2200. In one implementation, the processor 2210 is asingle-threaded processor. In another implementation, the processor 2210is a multi-threaded processor. The processor 2210 is capable ofprocessing instructions stored in the memory 2220 or on the storagedevice 2230 to display graphical information for a user interface on theinput/output device 2240.

The memory 2220 stores information within the system 2200. In oneimplementation, the memory 2220 is a computer-readable medium. In oneimplementation, the memory 2220 is a volatile memory unit. In anotherimplementation, the memory 2220 is a non-volatile memory unit.

The storage device 2230 is capable of providing mass storage for thesystem 2200. In one implementation, the storage device 2230 is acomputer-readable medium. In various different implementations, thestorage device 2230 may be a floppy disk device, a hard disk device, anoptical disk device, or a tape device.

The input/output device 2240 provides input/output operations for thesystem 2200. In one implementation, the input/output device 2240includes a keyboard and/or pointing device. In another implementation,the input/output device 2240 includes a display unit for displayinggraphical user interfaces.

The features described can be implemented in digital electroniccircuitry, or in computer hardware, firmware, software, or incombinations of them. The apparatus can be implemented in a computerprogram product tangibly embodied in an information carrier, e.g., in amachine-readable storage device for execution by a programmableprocessor; and method steps can be performed by a programmable processorexecuting a program of instructions to perform functions of thedescribed implementations by operating on input data and generatingoutput. The described features can be implemented advantageously in oneor more computer programs that are executable on a programmable systemincluding at least one programmable processor coupled to receive dataand instructions from, and to transmit data and instructions to, a datastorage system, at least one input device, and at least one outputdevice. A computer program is a set of instructions that can be used,directly or indirectly, in a computer to perform a certain activity orbring about a certain result. A computer program can be written in anyform of programming language, including compiled or interpretedlanguages, and it can be deployed in any form, including as astand-alone program or as a module, component, subroutine, or other unitsuitable for use in a computing environment.

Suitable processors for the execution of a program of instructionsinclude, by way of example, both general and special purposemicroprocessors, and the sole processor or one of multiple processors ofany kind of computer. Generally, a processor will receive instructionsand data from a read-only memory or a random access memory or both. Theessential elements of a computer are a processor for executinginstructions and one or more memories for storing instructions and data.Generally, a computer will also include, or be operatively coupled tocommunicate with, one or more mass storage devices for storing datafiles; such devices include magnetic disks, such as internal hard disksand removable disks; magneto-optical disks; and optical disks. Storagedevices suitable for tangibly embodying computer program instructionsand data include all forms of non-volatile memory, including by way ofexample semiconductor memory devices, such as EPROM, EEPROM, and flashmemory devices; magnetic disks such as internal hard disks and removabledisks; magneto-optical disks; and CD-ROM and DVD-ROM disks. Theprocessor and the memory can be supplemented by, or incorporated in,ASICs (application-specific integrated circuits).

To provide for interaction with a user, the features can be implementedon a computer having a display device such as a CRT (cathode ray tube)or LCD (liquid crystal display) monitor for displaying information tothe user and a keyboard and a pointing device such as a mouse or atrackball by which the user can provide input to the computer.

The features can be implemented in a computer system that includes aback-end component, such as a data server, or that includes a middlewarecomponent, such as an application server or an Internet server, or thatincludes a front-end component, such as a client computer having agraphical user interface or an Internet browser, or any combination ofthem. The components of the system can be connected by any form ormedium of digital data communication such as a communication network.Examples of communication networks include, e.g., a LAN, a WAN, and thecomputers and networks forming the Internet.

The computer system can include clients and servers. A client and serverare generally remote from each other and typically interact through anetwork, such as the described one. The relationship of client andserver arises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other.

FIG. 23 is a diagram of an example steam map 2300. In someimplementations, the steam map 2300 may be provided by a turbinemanufacturer to describe the parameters of a turbine (e.g., the exampleturbine 912 of FIG. 9). In some implementations, the steam map 2300 maybe determined from turbine parameter information provided by the turbinemanufacturer.

The steam map 2300 includes points A, B, and C. K_(x) coefficient valuescan be determined based on these three points, A, B, and C. In generalterms, K₁ is the slope of line CA, K₂ can be solved as the amount ofchange in HP (e.g., Y-axis), from HB to the HP value for the line CAsolved for an S value=SB over 100 (e.g., full P range). K₃ is the Yintercept of line CA. K₄ is the full LP range (e.g., 100) divided by thechange in S from point A to point C. K₅ is the change in LP from point Bto the point where line CA is intersected by a vertical line from pointB (e.g., full P range). K₆ is the LP position at the Y intercept of lineCA (e.g., P=0 and S=0). In some implementations, K₆ can be found similarto above as the ratio of two distances.

Point A can be described by (A_x, A_y), where A_x and A_y are the x andy axis values for point A. Point B can be described by (B_x, B_y), whereB_x and B_y are the x and y axis values for point B. Point C can bedescribed by (C_x, C_y), where C_x and C_y are the x and y axis valuesfor point C. K_(x) coefficients can be determined as:

K ₁=(C_y−A_y)/(C_x−A_x)

K ₃ =A_y−A_x*K ₁

K ₂=(B_y−K ₃ −K ₁ *B_x)/100

K ₄=100/(A_x−C_x)

K ₆ =−K ₄ *C_x

K ₅=(B_x*K ₄ +K ₆)/−100

Although a few implementations have been described in detail above,other modifications are possible. For example, the logic flows depictedin the figures do not require the particular order shown, or sequentialorder, to achieve desirable results. In addition, other steps may beprovided, or steps may be eliminated, from the described flows, andother components may be added to, or removed from, the describedsystems. Accordingly, other implementations are within the scope of thefollowing claims.

What is claimed is:
 1. A method for operating a turbine comprising:receiving, at a ratio controller, one or more turbine response valuesbased on: a first process output value (S_(out)) of a first actuatorcontroller, the first process output value based on a first processinput value (S_(in)) and at least one first control parameter selectedfrom a group comprising a proportional gain value, an integral gainvalue, and a derivative gain value, wherein the first actuatorcontroller comprises a first parameter controller; and a second processoutput value (P_(out)) of a second actuator controller, the secondprocess output value based on a second process input value (P_(in)) andat least one second control parameter selected from the group, whereinthe second actuator controller comprises a second parameter controller;providing, by the ratio controller and to the first actuator controller,the first process input value as a predetermined first constant setpoint value; varying, by the ratio controller and to the second actuatorcontroller, the second process input value to a plurality ofpredetermined first set point values; receiving, by the second parametercontroller and for one or more of the first set point values, one ormore first updated turbine response values as the turbine responsevalues; determining, by the second parameter controller, at least onethird control parameter selected from the group based on the turbineresponse values; providing, by the second parameter controller and tothe second actuator controller, the third control parameter as thesecond control parameter; providing, by the ratio controller and to thesecond actuator controller, the second process input value as apredetermined second constant set point value; varying, by the ratiocontroller and to the first actuator controller, the first process inputvalue to a plurality of predetermined second set point values;receiving, by the first parameter controller and for one or more of thesecond set point values, one or more second updated turbine responsevalues as the turbine response values; determining, by the firstparameter controller, at least one fourth control parameter selectedfrom the group based on the turbine response values; and providing, bythe first parameter controller and to the first actuator controller, thefourth control parameter as the first control parameter.
 2. The methodof claim 1, further comprising controlling, by the first parametercontroller and the second parameter controller, the turbine based on thefirst process output value and the second process output value.
 3. Themethod of claim 1, further comprising: determining a first controloutput value (HP) based on the first process output value (S_(out)), thesecond process output value (P_(out)), and one or more ratio parameters(K_(x)); determining a second control output value (LP) based on thefirst process output value (S_(out)), the second process output value(P_(out)), and the one or more ratio parameters; and controlling, by theratio controller, the turbine based on the first control output valueand the second control output value.
 4. The method of claim 3, whereinthe one or more ratio parameters (K_(x)) comprises a collection of ratioparameters K₁, K₂, K₃, K₄, K₅, and K₆, the first control output (HP) isgiven by the equation HP=K₁S_(out)+K₂P_(out)+K₃, and the second controloutput (LP) is given by the equation LP=K₄S_(out)+K₅P_(out)+K₆.
 5. Themethod of claim 1, wherein the first parameter controller controls afirst component of the turbine effecting the turbine response values,and the second parameter controller controls a second component of theturbine effecting the turbine response values.
 6. A turbine controllercomprising: an input port; an output port; a ratio controller; memorystoring instructions that are executable; and one or more processingdevices to execute the instructions to perform operations comprising:receiving, at the ratio controller, one or more turbine response valuesbased on: a first process output value (S_(out)) of a first actuatorcontroller, the first process output value based on a first processinput value (S_(in)) and at least one first control parameter selectedfrom a group comprising a proportional gain value, an integral gainvalue, and a derivative gain value, wherein the first actuatorcontroller comprises a first parameter controller; and a second processoutput value (P_(out)) of a second actuator controller, the secondprocess output value based on a second process input value (P_(in)) andat least one second control parameter selected from the group, whereinthe second actuator controller comprises a second parameter controller;providing, by the ratio controller and to the first actuator controller,the first process input value as a predetermined first constant setpoint value; varying, by the ratio controller and to the second actuatorcontroller, the second process input value to a plurality ofpredetermined first set point values; receiving, by the second parametercontroller and for one or more of the first set point values, one ormore first updated turbine response values as the turbine responsevalues; determining, by the second parameter controller, at least onethird control parameter selected from the group based on the turbineresponse values; providing, by the second parameter controller and tothe second actuator controller, the third control parameter as thesecond control parameter; providing, by the ratio controller and to thesecond actuator controller, the second process input value as apredetermined second constant set point value; varying, by the ratiocontroller and to the first actuator controller, the first process inputvalue to a plurality of predetermined second set point values;receiving, by the first parameter controller and for one or more of thesecond set point values, one or more second updated turbine responsevalues as the turbine response values; determining, by the firstparameter controller, at least one fourth control parameter selectedfrom the group based on the turbine response values; and providing, bythe first parameter controller and to the first actuator controller, thefourth control parameter as the first control parameter.
 7. The turbinecontroller of claim 6, the operations further comprising controlling, bythe first parameter controller and the second parameter controller, theturbine based on the first process output value and the second processoutput value.
 8. The turbine controller of claim 6, the operationsfurther comprising: determining a first control output value (HP) basedon the first process output value (S_(out)), the second process outputvalue (P_(out)), and one or more ratio parameters (K_(x)); determining asecond control output value (LP) based on the first process output value(S_(out)), the second process output value (P_(out)), and the ratioparameters; and controlling, by the ratio controller, the turbine basedon the first control output value and the second control output value.9. The turbine controller of claim 8, wherein the one or more ratioparameters (K_(x)) comprises a collection of ratio parameters K₁, K₂,K₃, K₄, K₅, and K₆, the first control output (HP) is given by theequation HP=K₁S_(out)+K₂P_(out)+K₃, and the second control output (LP)is given by the equation LP=K₄S_(out)+K₅P_(out)+K₆.
 10. The turbinecontroller of claim 6, wherein the first parameter controller controls afirst component of the turbine effecting the turbine response values,and the second parameter controller controls a second component of theturbine effecting the turbine response values.
 11. A turbine systemcomprising: a first process controller configured to perform a controlalgorithm based on at least one first control parameter selected from agroup comprising a proportional gain value, an integral gain value, anda derivative value; a second process controller configured to perform acontrol algorithm based on at least one second control parameterselected from a group comprising a proportional gain value, an integralgain value, and a derivative value; a ratio controller configured toperform a parameter adjustment algorithm; a turbine having assembledthereto a turbine output sensor in communication with the first processcontroller, the second process controller, and the ratio controller;wherein the parameter adjustment algorithm is configured to performoperations comprising: receiving, at the ratio controller, one or moreturbine response values based on: a first process output value (S_(out))of a first actuator controller, the first process output value based ona first process input value (S_(in)) and at least one first controlparameter selected from a group comprising a proportional gain value, anintegral gain value, and a derivative gain value, wherein the firstactuator controller comprises a first parameter controller; and a secondprocess output value (P_(out)) of a second actuator controller, thesecond process output value based on a second process input value(P_(in)) and at least one second control parameter selected from thegroup, wherein the second actuator controller comprises a secondparameter controller; providing, by the ratio controller and to thefirst actuator controller, the first process input value as apredetermined first constant set point value; varying, by the ratiocontroller and to the second actuator controller, the second processinput value to a plurality of predetermined first set point values;receiving, by the second parameter controller and for one or more of thefirst set point values, one or more first updated turbine responsevalues as the turbine response values; determining, by the secondparameter controller, at least one third control parameter selected fromthe group based on the turbine response values; providing, by the secondparameter controller and to the second actuator controller, the thirdcontrol parameter as the second control parameter; providing, by theratio controller and to the second actuator controller, the secondprocess input value as a predetermined second constant set point value;varying, by the ratio controller and to the first actuator controller,the first process input value to a plurality of predetermined second setpoint values; receiving, by the first parameter controller and for oneor more of the second set point values, one or more second updatedturbine response values as the turbine response values; determining, bythe first parameter controller, at least one fourth control parameterselected from the group based on the turbine response values; andproviding, by the first parameter controller and to the first actuatorcontroller, the fourth control parameter as the first control parameter.12. The turbine system of claim 11, the operations further comprisingcontrolling, by the first parameter controller and the second parametercontroller, the turbine based on the first process output value and thesecond process output value.
 13. The turbine system of claim 11, theoperations further comprising: determining a first control output value(HP) based on the first process output value (S_(out)), the secondprocess output value (P_(out)), and one or more ratio parameters(K_(x)); determining a second control output value (LP) based on thefirst process output value (S_(out)), the second process output value(P_(out)), and the ratio parameters; and controlling, by the ratiocontroller, the turbine based on the first control output value and thesecond control output value.
 14. The turbine system of claim 13, whereinthe one or more ratio parameters (K_(x)) comprises a collection of ratioparameters K₁, K₂, K₃, K₄, K₅, and K₆, the first control output (HP) isgiven by the equation HP=K₁S_(out)+K₂P_(out)+K₃, and the second controloutput (LP) is given by the equation LP=K₄S_(out)+K₅P_(out)+K₆.
 15. Theturbine system of claim 11, wherein the first parameter controllercontrols a first component of the turbine effecting the turbine responsevalues, and the second parameter controller controls a second componentof the turbine effecting the turbine response values.
 16. A computerreadable medium storing instructions that, when executed by one or moreprocessors, cause the one or more processors to perform operationscomprising: receiving, at a ratio controller, one or more turbineresponse values based on: a first process output value (S_(out)) of afirst actuator controller, the first process output value based on afirst process input value (S_(in)) and at least one first controlparameter selected from a group comprising a proportional gain value, anintegral gain value, and a derivative gain value, wherein the firstactuator controller comprises a first parameter controller; and a secondprocess output value (P_(out)) of a second actuator controller, thesecond process output value based on a second process input value(P_(in)) and at least one second control parameter selected from thegroup, wherein the second actuator controller comprises a secondparameter controller; providing, by the ratio controller and to thefirst actuator controller, the first process input value as apredetermined first constant set point value; varying, by the ratiocontroller and to the second actuator controller, the second processinput value to a plurality of predetermined first set point values;receiving, by the second parameter controller and for one or more of thefirst set point values, one or more first updated turbine responsevalues as the turbine response values; determining, by the secondparameter controller, at least one third control parameter selected fromthe group based on the turbine response values; providing, by the secondparameter controller and to the second actuator controller, the thirdcontrol parameter as the second control parameter; providing, by theratio controller and to the second actuator controller, the secondprocess input value as a predetermined second constant set point value;varying, by the ratio controller and to the first actuator controller,the first process input value to a plurality of predetermined second setpoint values; receiving, by the first parameter controller and for oneor more of the second set point values, one or more second updatedturbine response values as the turbine response values; determining, bythe first parameter controller, at least one fourth control parameterselected from the group based on the turbine response values; andproviding, by the first parameter controller and to the first actuatorcontroller, the fourth control parameter as the first control parameter.17. The computer readable medium of claim 16, the operations furthercomprising controlling, by the first parameter controller and the secondparameter controller, the turbine based on the first process outputvalue and the second process output value.
 18. The computer readablemedium of claim 16, the operations further comprising: determining afirst control output value (HP) based on the first process output value(S_(out)), the second process output value (P_(out)), and the ratioparameters; determining a second control output value (LP) based on thefirst process output value (S_(out)), the second process output value(P_(out)), and the ratio parameters; and controlling, by the ratiocontroller, the turbine based on the first control output value and thesecond control output value.
 19. The computer readable medium of claim18, wherein the one or more ratio parameters (K_(x)) comprises acollection of ratio parameters K₁, K₂, K₃, K₄, K₅, and K₆, the firstcontrol output (HP) is given by the equation HP=K₁S_(out)+K₂P_(out)+K₃,and the second control output (LP) is given by the equationLP=K₄S_(out)+K₅P_(out)+K₆.
 20. The computer readable medium of claim 16,wherein the first parameter controller controls a first component of theturbine effecting the turbine response values, and the second parametercontroller controls a second component of the turbine effecting theturbine response values.